{"id":"W4323780118","doi":"10.1007/978-3-031-28032-0_45","title":"The Rural Informatization Policies in China: The Power Dynamics and Policy Instruments","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"China's Socioeconomic Reforms and Governance","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Informatization; China; Government (linguistics); Christian ministry; Power (physics); System dynamics; Policy analysis; Environmental economics; Rural area; Computer science; Public administration; Political science; Economics; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002308179,0.0002809134,0.0001990766,0.002085814,0.002102214,0.002982324,0.0004824681,0.0004891882,0.002731484],"category_scores_gemma":[0.002583367,0.000183705,0.0001471106,0.005299087,0.002621305,0.002458032,0.001391325,0.0005792693,0.0001708443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01269421,"about_ca_system_score_gemma":0.01566275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04237853,"about_ca_topic_score_gemma":0.05212431,"domain_scores_codex":[0.9987239,0.0004034853,0.00007331598,0.0001513478,0.0003234655,0.0003244254],"domain_scores_gemma":[0.9986157,0.0005146278,0.0003235113,0.00008105504,0.0002395648,0.0002254595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000188056,0.0001278549,0.1093344,0.000984498,0.0000694086,0.0007420761,0.03488161,0.009041182,0.003522647,0.5675576,0.0179839,0.2555668],"study_design_scores_gemma":[0.00007131862,0.0001942505,0.5544515,0.0007615768,0.00008611975,0.0002272002,0.03193199,0.01858784,0.004156814,0.09291661,0.2964925,0.0001221296],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8547255,0.006066827,0.004213038,0.01548676,0.0001281349,0.0001861569,0.0006151494,0.0001331329,0.1184452],"genre_scores_gemma":[0.9860534,0.0018237,0.0009417285,0.0002183126,0.00004244846,0.00004640946,0.0001351916,0.000009000419,0.01072974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04237853,"threshold_uncertainty_score":0.09210336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006453846375701587,"score_gpt":0.2537186055279361,"score_spread":0.2472647591522345,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}